In the case of linear scanning images, an observation location and speed, an observation posture and an observation angle given as auxiliary data are generally inaccurate. Accordingly, when the geometry of the linear scanning images is recovered using the auxiliary data, geometric distortion occurs, with the result that accurate locations cannot be determined from the images. In particular, in the case of satellite images, the situation is more serious. In order to correct the geometric distortion of linear scanning images, ground control points (GCPs), to which ground points corresponding to image points have been allocated, are used. Geometry is recovered using a few or more ground control points, and then ground coordinates are allocated to images based on the recovered geometry, thereby allocating accurate ground locations to the images.
In general, ground control points are acquired directly through actual measurement using GPS equipment. However, because of a constraint condition requiring a visit to an actual place, considerable time and cost are required, and actual measurement itself cannot be performed in an inaccessible place, such as North Korea. For this reason, a variety of types of research into a method of reducing the number of ground control points and the replacement of ground control points have been conducted.
One of the methods is a method of reducing the number of ground control points by adjusting only the photographing angle (LOS vector) of the sensor of photographing equipment. However, the use of a small number of ground control points is problematic in that an error in the selection of image points in images and distortion attributable to the location error of ground points may occur and also the above method cannot be used in an area in which ground control points cannot be obtained.
Therefore, Korean Patent No. 10-0870894 describes a method for automatic geometric correction of linear pushbroom images, which is capable of automatically extracting ground control points using digital elevation data provided by a digital elevation model, allocating accurate ground coordinates to each set of image coordinates of images, reducing the time and cost required for geometric correction, and improving the accuracy of ground coordinates.
However, most high-resolution satellite images provide data including RPCs to enable 3D location determination in a target area. Since image geometry calculated as RPCs includes a specific number of systematic errors, technology for correcting the systematic errors and then allocating accurate ground coordinates to each set of image coordinates of images is required.
Meanwhile, research that has been conducted so far is disadvantageous in that data clips requiring high costs in an early stage, such as geometrically corrected satellite images, Synthetic Aperture Radar (SAR) images, Light Detection And Ranging (LIDAR) data, a Ground Control Point (GCP) chip, a digital map, etc., are prerequisites, manual work is partially required to make the coordinate systems of images uniform when multi-sensor data, such as SAR images, is used, and a processing process is relatively very complicated. Furthermore, the accuracy of performed final geometric correction is also unsatisfactory.